\author{Daniel L Elliott}
\email{dane@cs.colostate.edu}
\url{www.cs.colostate.edu/~dane}
\name{makeMoG}
\alias{MoG learning via EM}
\alias{makeMoG}
\title{Mog learning}
\description{
  Handles iterating over EM update rules (both E and M steps) until
  convergence criteria is met.
  Returns a MoG list.}
\value{
  \item{$MoGmodel$Pc}{Vector of probabilites.}
  \item{$MoGmodel$$mu}{Matrix of cluster means stored by column.}
  \item{$MoGmodel$Sigma}{List of covariance matrices: one for each
    cluster.}  
  \item{$standardizeF}{Function used to standardize the inputs.}
  }
\arguments{
  \item{X}{Data set matrix with elements by column.}
  \item{C}{Number of clusters.}
  \item{initF}{The function to use to initialize the model}
  \item{covRegF}{The function to use to perform covariance
    regularization.  Function should take entire model as input and
    return entire model.}
}
% \usage{initMoGrandomDatum(X,C)}
\seealso{initMoG,shrinkage,standardization}